Introduction The image recorded by a camera depends on three factors: The physical content of the scene, the illumination incident on the scene, and the characteristics

Image alignment should be based on features that are robust with respect to phenomena such as global illumination changes, shading variations, and local highlights. While hue provides a natural degree of invariance to these phenomena, we show that it has several deficiencies in terms of gradient-based image alignment. To overcome these limitations, we introduce a 2D representation for hue that ...

Changing illumination constitutes a serious challenge for video segmentation algorithms, especially in outdoor scenes under cloudy conditions. Rapid illumination changes, e.g. caused by varying cloud cover, often cause existing segmentation algorithms to erroneously classify large parts of the image as foreground. Here a method that extends existing segmentation algorithms by detecting illumina...

Image relighting is to change the illumination of an image to a target illumination effect without known the original scene geometry, material information and illumination condition. We propose a novel outdoor scene relighting method, which needs only a single reference image and is based on material constrained layer decomposition. Firstly, the material map is extracted from the input image. T...

Classifying color textures under varying illumination sources remains challenging. To address this issue, this paper introduces a new descriptor for color texture classification, which is robust to changes in the scene illumination. The proposed descriptor, named Color Intensity Local Mapped Pattern (CILMP), incorporates relevant information about the color and texture patterns from the image i...